code: def super_lm_tpu_memtest():
      """Crazy set of hyperparameters to test memory optimizations.
  
      Quality will be very poor due to lack of attention layers.
      853M parameters
      This seems to run on TPU for languagemodel_lm1b8k_packed as of 2018-01-19.
  
      Returns:
        An hparams object.
      """
      hparams = super_lm_base()
      hparams.num_model_shards = 1
      hparams.layers = "ffn," * 8
      hparams.hidden_size = 4096
      hparams.filter_size = 12000
      hparams.batch_size = 512
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from six.moves import range
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import diet
  from tensor2tensor.utils import expert_utils
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 13 for calling a global function with example usage: super_lm_tpu_memtest() and returns: hparams